Blog Posts

Overview of Analysis Process and Analyzers in Elasticsearch

An inverted index is a data structure that consists of a list of all unique words and list of the documents in which it appears. New documents are analyzed and then stored as inverted indexes, to allow very fast full-text searches.

Analysis is the process of converting the text into tokens and normalizing tockens before adding them into an inverted index. When we do a full text search, we search the inverted index rather than on the actual documents. So both the indexed text and the query string must be analyzed.

Introduction to Mappings in Elasticsearch

Mapping defines the types, formats etc. for different fields in an Elasticsearch document. Mapping also defines various ways in which fields / types behave in different situations (e.g. dynamic mapping allows creation of types dynamically). Mpping may also denote how a document’s metadata associated (e.g. _index, _type, _id, and _source ) is treated. 

Mappings are defined for each type and with ES 6.2 there can be only one type per index. Therefore mappings are defined per index.

 

Different Ways to Install, Configure and Use Elasticsearch

There are different ways to install, configure and use elasticsearch. Working with a real Elasticsearch cluster is essential for following all notes in this section. 

 

Elastic Cloud (from Elastic.co)

Elastic Cloud is the hosted version of Elasticsearch and Kibana from Elastic.co. You can get started with Elastic Cloud here.

Continuous Integration, Continuous Deployment and Continuous Delivery

Continuous Integration (CI) is a development practice that requires developers to integrate code early and often. Code is integrated into a shared repository several times a day. Each check-in is then verified by an automated build, thus providing fast and automated feedback on the correctness of your application every time there is a change of code.

What is ZooKeeper?

ZooKeeper is an application library that allows distributed processes to coordinate with each other through a shared hierarchical name space of data registers; these data registers are called as znodes. 

ZooKeeper was designed to store coordination data such as status information, configuration, location information, and so on.

ZooKeeper was a sub-project of Hadoop but is now a top-level project in its own right.

Amazon Elasticsearch Service - Learning Plans

With the previous notes from the current book (Amazon Elasticsearch Service) and Elasticsearch Essentials, you should have decent understanding of Elasticsearch. Next, we will try to learn Amazon ES in deep.

Following are some of the links that will help start that journey to master Amazon ES:

  1. Creating and Configuring Amazon Elasticsearch Service Domains

Introduction to Java Clients for Elasticsearch

Java programmers had two choices when communicating with Elasticsearch: they could use either the REST API over HTTP, or the internal Java API (aka transport client), which is used by Elasticsearch itself for node-to-node communication. When using the HTTP rest client, Elasticsearch parses the JSON to Java objects and then use the internal Java API, and when we use the internal Java API we use those internal Java objects directly. 

 

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About

CloudMaterials.com is my latest blog to share my notes and learning materials on Cloud and Data Analytics. My current focus is on Amazon Web Servivces.

I like to write and always try to document what I learn. I believe that knowledge is useless unless you share it; the more you share, the more you learn.

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